Mumbai-based stressed receivables management firm Moneytor has raised an undisclosed amount of funding from 500 Startups, fintech accelerator ISME ACE. The round also saw the participation of a few angel investors including Satyen Kothari, founder and CEO of Cube Consumer Services and former executives of Dun & Bradsteet.

With this fundraise, Moneytor is looking to automate and digitise all the processes related to debt collection, post a consumer or organisation defaulting on their loans. This is a major hurdle that most financial institutions and organisations with business receivables face as they strive to get a defaulter to pay back while trying to maintain a consistency in communication, especially when outsourcing to third-party agencies. This is the problem that Moneytor is looking to tackle, as it brings transparency to the entire process.

Commenting on the investments, Shalini Prakash, Venture Partner at500 Startups stated, “. Moneytor’s automated debt- collection and recovery product solves a big pain point for all financial institutions. By adopting digital channels and predictive analytics, they are tackling a widespread problem for the industry.”

Founded by Anubhav Singh and Ayush Srivastava in 2017, Moneytor is leveraging machine learning and proprietary algorithms to make the currently fragmented stressed receivables market more efficient, improve default recovery rates and, in the long run, be able to price such portfolios correctly.

The Startup has also been shortlisted by the Fintech Valley Accelerator for its first cohort.

Anubhav Singh, co-founder of Moneytor stated, “Earlier, It was impossible to agree to a price with any financial institution for a portfolio, as there was no basis on which to value these accounts. There was no demographic data or information about communication with particular accounts, for anyone to make a decision on buying these portfolios.”

Providing an end-to-end solution through its SaaS platform, including last mile connectivity to defaulters, Moneytor is looking to utilise its proprietary machine learning algorithms to help improve operational efficiency and recovery rates by figuring out potential settlement offers for each defaulter.

By automating the process using an in-house communication tool and decision-making engine, which suggests appropriate settlements to users based on their profile, Moneytor helps make the process quicker and efficient, claims the company.

However, by offering an automatisation of the collection process, settlement decision making and communication, Moneytor has made a separate space for its offerings in fintech. Having raised the Seed funding, within a year of its foundation, it will be interesting see how Moneytor differentiates and customises its solution further!

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